Incorporating geometric ray tracing to generate initial conditions for intensity modulated arc therapy optimization
Bibliographic record
Abstract
PURPOSE AND BACKGROUND: Intensity modulated arc therapy (IMAT) is a rotational variant of Intensity modulated radiation therapy (IMRT) that is achieved by allowing the multileaf collimator (MLC) positions to vary as the gantry rotates around the patient. This work describes a method to generate an IMAT plan through the use of a fast ray tracing technique based on dosimetric and geometric information for setting initial MLC leaf positions prior to final IMAT optimization. METHODS AND MATERIALS: Three steps were used to generate an IMAT plan. The first step was to generate arcs based on anatomical contours. The second step was to generate ray importance factor (RIF) maps by ray tracing the dose distribution inside the planning target volume (PTV) to modify the MLC leaf positions of the anatomical arcs to reduce the maximum dose inside the PTV. The RIF maps were also segmented to create a new set of arcs to improve the dose to low dose voxels within the PTV. In the third step, the MLC leaf positions from all arcs were put through a leaf position optimization (LPO) algorithm and brought into a fast Monte Carlo dose calculation engine for a final dose calculation. The method was applied to two phantom cases, a clinical prostate case and the Radiological Physics Center (RPC)'s head and neck phantom. The authors assessed the plan improvements achieved by each step and compared plans with and without using RIF. They also compared the IMAT plan with an IMRT plan for the RPC phantom. RESULTS: All plans that incorporated RIF and LPO had lower objective function values than those that incorporated LPO only. The objective function value was reduced by about 15% after the generation of RIF arcs and 52% after generation of RIF arcs and leaf position optimization. The IMAT plan for the RPC phantom had similar dose coverage for PTV1 and PTV2 (the same dose volume histogram curves), however, slightly lower dose to the normal tissues compared to a six-field IMRT plan. CONCLUSION: The use of a ray importance factor can generate initial IMAT arcs efficiently for further MLC leaf position optimization to obtain more favorable IMAT plan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".